Freshwater genome-reduced bacteria exhibit pervasive episodes of adaptive stasis.
Lucas Serra MoncadasCyrill HoferPaul-Adrian BulzuJakob PernthalerAdrian-Ştefan AndreiPublished in: Nature communications (2024)
The emergence of bacterial species is rooted in their inherent potential for continuous evolution and adaptation to an ever-changing ecological landscape. The adaptive capacity of most species frequently resides within the repertoire of genes encoding the secreted proteome (SP), as it serves as a primary interface used to regulate survival/reproduction strategies. Here, by applying evolutionary genomics approaches to metagenomics data, we show that abundant freshwater bacteria exhibit biphasic adaptation states linked to the eco-evolutionary processes governing their genome sizes. While species with average to large genomes adhere to the dominant paradigm of evolution through niche adaptation by reducing the evolutionary pressure on their SPs (via the augmentation of functionally redundant genes that buffer mutational fitness loss) and increasing the phylogenetic distance of recombination events, most of the genome-reduced species exhibit a nonconforming state. In contrast, their SPs reflect a combination of low functional redundancy and high selection pressure, resulting in significantly higher levels of conservation and invariance. Our findings indicate that although niche adaptation is the principal mechanism driving speciation, freshwater genome-reduced bacteria often experience extended periods of adaptive stasis. Understanding the adaptive state of microbial species will lead to a better comprehension of their spatiotemporal dynamics, biogeography, and resilience to global change.
Keyphrases
- genome wide
- dna methylation
- climate change
- genetic diversity
- microbial community
- magnetic resonance imaging
- single cell
- physical activity
- risk assessment
- computed tomography
- gene expression
- human health
- depressive symptoms
- dna damage
- body composition
- electronic health record
- machine learning
- deep learning
- artificial intelligence
- soft tissue
- genome wide identification
- genome wide analysis
- free survival
- water quality